A Study on Occupational Health and Safety Practices on Construction Site Workers for Finding Discomfort Level
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- Matthias Schonlau, 2004. "Visualizing non-hierarchical and hierarchical cluster analyses with clustergrams," Computational Statistics, Springer, vol. 19(1), pages 95-111, February.
- Antonopoulos, Ioannis & Robu, Valentin & Couraud, Benoit & Kirli, Desen & Norbu, Sonam & Kiprakis, Aristides & Flynn, David & Elizondo-Gonzalez, Sergio & Wattam, Steve, 2020. "Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
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